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    <title>nanstdev</title>
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    <div align="right">Last update : 20/12/2004</div>
    <p>
      <b>nanstdev</b> -  standard deviation (ignoring the NANs).  </p>
    <h3>
      <font color="blue">Calling Sequence</font>
    </h3>
    <dl>
      <dd>
        <tt>s=nanstdev(x)  </tt>
      </dd>
      <dd>
        <tt>s=nanstdev(x,'r') or m=nanstdev(x,1)  </tt>
      </dd>
      <dd>
        <tt>s=nanstdev(x,'c') or m=nanstdev(x,2)  </tt>
      </dd>
    </dl>
    <h3>
      <font color="blue">Parameters</font>
    </h3>
    <ul>
      <li>
        <tt>
          <b>x</b>
        </tt>real or complex vector or matrix</li>
    </ul>
    <h3>
      <font color="blue">Description</font>
    </h3>
    <p>
    This function   computes the standard  deviation  of the
    values of  a vector or  matrix   <tt>
        <b> x</b>
      </tt> (ignoring  the
    NANs).</p>
    <p>
    For a vector or a matrix <tt>
        <b> x</b>
      </tt>, <tt>
        <b> s=nanstdev(x)</b>
      </tt>
    returns in the scalar  <tt>
        <b> s</b>
      </tt> the  standard deviation
    of all the entries of <tt>
        <b>x</b>
      </tt> (ignoring the NANs).</p>
    <p>
      <tt>
        <b>s=nanstdev(x,'r')</b>
      </tt>        (or,  equivalently,  
    <tt>
        <b>  s=nanstdev(x,1) </b>
      </tt>) is  the rowwise standard deviation.
    It returns in each entry of the row  vector <tt>
        <b> s</b>
      </tt> the
    standard deviation of each column of <tt>
        <b> x</b>
      </tt> (ignoring
    the NANs).</p>
    <p>
      <tt>
        <b>s=nanstdev(x,'c')</b>
      </tt>          (or,      equivalently,
    <tt>
        <b>s=nanstdev(x,2)</b>
      </tt>)   is the columnwise      standard
    deviation. It returns in each entry of the column vector
    <tt>
        <b>s</b>
      </tt> the standard  deviation of  each row of  <tt>
        <b>x</b>
      </tt>
    (ignoring the NANs).</p>
    <p>
    In Labostat, NAN values stand for missing values in tables.</p>
    <h3>
      <font color="blue">Examples</font>
    </h3>
    <pre>


x=[0.2113249 0.0002211 0.6653811;
   0.7560439 %nan      0.6283918;
   0.3       0.2       0.5      ];
s=nanstdev(x)
s=nanstdev(x,'r')
s=nanstdev(x,'c')
 
  </pre>
    <h3>
      <font color="blue">Author</font>
    </h3>
    <p> Carlos Klimann</p>
    <h3>
      <font color="blue">Bibliography</font>
    </h3>
    <p>
    Wonacott, T.H. &amp; Wonacott, R.J.; Introductory Statistics, fifth edition, J.Wiley &amp; Sons, 1990.</p>
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